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Articles

Analysis and Classification of Three Trimesters during Normal Pregnancy Using Bispectrum

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Abstract

This study presents the analysis and classification of maternal status during healthy pregnancy and postpartum using bispectral features of heart rate variability (HRV). Bispectral analysis is applied to HRV to extract a total of 11 features out of which only 6 significantly different feature values are used to classify the subjects into three trimesters during pregnancy and postpartum. In particular, bispectrum patterns indicate the presence of higher phase coupling during postpartum as compared to the pregnancy group. The decreased phase coupling is observed as pregnancy progresses that refer to the decreased nonlinear interactions during pregnancy. This infers that the pregnancy is characterized by decreased HRV due to a reduced vagal tone instead of increased sympathetic tone. The six selected features are used as input to the k-nearest neighbour (KNN), Gaussian mixture model (GMM) and probabilistic neural network (PNN) classifiers for data classification. The performance of the classifiers are measured based on the accuracy of classification. The classification rate obtained for KNN, GMM and PNN classifiers are 85.94%, 85.94% and 89.74% respectively. We conclude that the bispectral features with PNN classifier is better suitable for the classification of the three trimesters during pregnancy and postpartum.

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Notes on contributors

S. T. Veerabhadrappa

S T Veerabhadrappa obtained Bachelor of electronics & communication engineering in 1994 from The National Institute of Engineering, Mysore. He obtained masters in biomedical engineering in 1998 from Manipal Institute of Technology, Manipal. He obtained PhD in 2016 from Indian Institute of Technology (IIT), Delhi, India He worked as lecturer in Electronics and Communication Engineering Department from 1995 to 2000 at SJM Institute of Technology, Chitradurga. Since 2001, he has been lecturer and at present associate professor in Electronics and Communication Engineering Department at JSS Academy of Technical Education, Bengaluru, Karnataka, India.

Anoop Lal Vyas

Anoop Lal Vyas obtained Bachelor of Technology in electrical engineering in 1972 and PhD in 1989 both from Indian Institute of Technology (IIT), Delhi. Since 1972 he has been working at IIT Delhi in the areas of sonar signal processing, underwater electronics and electronic systems and has coordinated a number of sponsored projects in these areas. He presently holds a position of professor and his interests include electronic instrumentation, smart sensors, body area networks, telemedicine and biomedical signal processing. Email: [email protected]

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